Dual arm manipulation—A survey

Recent advances in both anthropomorphic robots and bimanual industrial manipulators had led to an increased interest in the specific problems pertaining to dual arm manipulation. For the future, we foresee robots performing human-like tasks in both domestic and industrial settings. It is therefore natural to study specifics of dual arm manipulation in humans and methods for using the resulting knowledge in robot control. The related scientific problems range from low-level control to high level task planning and execution. This review aims to summarize the current state of the art from the heterogenous range of fields that study the different aspects of these problems specifically in dual arm manipulation.     

Structural shape optimization—A survey

This paper is a survey of structural shape optimization with an emphasis on techniques dealing with shape optimization of the boundaries of two- and three-dimensional bodies. Attention is focused on the special problems of structural shape optimization which are due to a finite element model which must change during the optimization process. These problems include the requirement for sophisticated automated mesh generation techniques and careful choice of design variables. They also include special problems in obtaining sufficiently accurate sensitivity derivatives.     

KZ1——A Prototype of Intelligent Operating System

This paper proposes an intelligent Operating System (IOS) as the next generation operating system.IOS integrates operating system with artificial intelligence technology,and its key feature is an intelligent man-machine communication mechanism which makes the computer systems more friendly.The concepts,functions and architecture of IOS are introduced and an experimental IOS called KZ1 is described in detail.     

Implementation of digital controllers—A survey

Stimulated by microprocessor technology there is increasing interest in the issues of digital control implementation. This paper reviews these issues, from algorithms through current hardware up to the various problems arising with non-ideal behaviour of digital controllers.     

Fractional cyber-neural systems — A brief survey

Neurotechnology has made great strides in the last 20 years. However, we still have a long way to go to commercialize many of these technologies as we lack a unified framework to study cyber-neural systems (CNS) that bring the hardware, software, and the neural system together. Dynamical systems play a key role in developing these technologies as they capture different aspects of the brain and provide insight into their function. Converging evidence suggests that fractional-order dynamical systems are advantageous in modeling neural systems because of their compact representation and accuracy in capturing the long-range memory exhibited in neural behavior. In this brief survey, we provide an overview of fractional CNS that entails fractional-order systems in the context of CNS. In particular, we introduce basic definitions required for the analysis and synthesis of fractional CNS, encompassing system identification, state estimation, and closed-loop control. Additionally, we provide an illustration of some applications in the context of CNS and draw some possible future research directions. Advancements in these three areas will be critical in developing the next generation of CNS, which will, ultimately, improve people’s quality of life.     

Software development cost estimation approaches — A survey

This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertise‐based techniques, learning‐oriented techniques, dynamics‐based models, regression‐based models, and composite‐Bayesian techniques for integrating expertise‐based and regression‐based models. Experience to date indicates that neural‐net and dynamics‐based techniques are less mature than the other classes of techniques, but that all classes of techniques are challenged by the rapid pace of change in software technology. The primary conclusion is that no single technique is best for all situations, and that a careful comparison of the results of several approaches is most likely to produce realistic estimates. This revised version was published online in June 2006 with corrections to the Cover Date.     

Robustness of nonlinear state feedback—A survey

A survey of robustness of nonlinear state feedback is given. For series perturbations there are fairly complete results, showing that under mild restrictions an optimal controller can tolerate an infinite increase in gain. For gain reductions there are some results for systems linear in the control. In particular there is a 50% reduction tolerance if the control penalty is quadratic. Usually the optimal controller cannot be computed exactly. There are some results showing the effects of truncation on the robustness. Essentially robustness is maintained but in a reduced (computable) part of the state space.     

Negative selection in anomaly detection—A survey

The remarkable ability to separate and identify self and non-self in a given problem space, makes negative selection a fascinating concept of artificial immune system. Therefore, negative selection has attracted research interest and is studied and explored for complex problem solving across different application areas. Anomaly detection in computer security is a thriving area of research and has witnessed various new explores involving different computational intelligence techniques. Negative selection with its core ability to detect self and non-self along with traits like adaptability, learning, robustness and faster response makes it a suitable and compelling concept for anomaly detection. Over the years, negative selection has evolved from its preliminary theories and it has embraced new improvements from computational intelligence in its several concepts. This paper intends to review various negative selection taxonomies, representations and matching techniques from inception to current scenario in anomaly detection. It attempts to critically evaluate and classify available literature to establish future areas of research for formulating potential solutions to mitigate the complex security challenges.     

Decomposition of binary images—A survey and comparison

We present an overview of the most important methods that decompose an arbitrary binary object into a union of rectangles. We describe a run-length encoding and its generalization, decompositions based on quadtrees, on mathematical morphology, on the distance transform, and a theoretically optimal decomposition based on a maximal matching in bipartite graphs. We compare their performance in image compression, in moment computation and in linear filtering. We show that the choice is always a compromise between the complexity and time/memory consumption. We give advice how to select an appropriate method in particular cases.     

Microcomputer control of high dynamic performance ac-drives—A survey

Alternating current machines, in particular induction motors, are of simple mechanical construction but have a nonlinear, highly interacting multivariable control structure. This has made it difficult in the past to design controlled ac-drives with high dynamic performance, similar to converter-fed dcdrives. A satisfactory solution of this problem has not been available until Blaschke formulated the principle of field orientation, where the machine is controlled in a moving frame of reference. This paper presents a survey of controlling acmachines for use in high dynamic performance drives including different types of machines and converters with their specific control characteristics. It is shown that by combining a suitable machine model with the principle of rotor- or field-orientation a unifying basis for the design of ac-drives is created. The complicated signal structure of the control systems can very effectively be handled by microelectronics, i.e. by using software instead of elaborate hardware. This is shown in the paper with the help of examples.     

Sensors and controllers location in distributed systems—A survey

A survey of the field of optimal sensors and/or controllers location for dynamical distributed parameter systems modelled by partial differential equations is presented. The recent contributions in this field are grouped according to the main goal for which the location problem is developed, namely: system identification, state estimation, and optimal control. In order to pose the sensors and controllers location problem, the semigroup approach for modelling distributed linear systems is briefly reviewed together with its equivalent (infinite dimensional) and approximate (finite dimensional) Fourier expansion representations. After presenting a concise general review of the several methods considered in the current literature, a classification of methods is also proposed. The main classifying factor concerns the use of N-modal approximation schemes, and the different stages of the optimization procedure in which they are required.     

Self-optimizing control – A survey

Self-optimizing control is a strategy for selecting controlled variables. It is distinguished by the fact that an economic objective function is adopted as a selection criterion. The aim is to systematically select the controlled variables such that by controlling them at constant setpoints, the impact of uncertain and varying disturbances on the economic optimality is minimized. If a selection leads to an acceptable economic loss compared to perfectly optimal operation then the chosen control structure is referred to as “self-optimizing”. In this comprehensive survey on methods for finding self-optimizing controlled variables we summarize the progress made during the last fifteen years. In particular, we present brute-force methods, local methods based on linearization, data and regression based methods, and methods for finding nonlinear controlled variables for polynomial systems. We also discuss important related topics such as handling changing active constraints. Finally, we point out open problems and directions for future research.     

How close are we to solving the problem of automated visual surveillance?

The problem of automated visual surveillance has spawned a lively research area, with 2005 seeing three conferences or workshops and special issues of two major journals devoted to the topic. These alone are responsible for somewhere in the region of 240 papers and posters on automated visual surveillance before we begin to count those presented in more general fora. Many of these systems and algorithms perform one small sub-part of the surveillance task, such as motion detection. But even with low level image processing tasks it is often difficult to compare systems on the basis of published results alone. This review paper aims to answer the difficult question “How close are we to developing surveillance related systems which are really useful?” The first section of this paper considers the question of surveillance in the real world: installations, systems and practises. The main body of the paper then considers existing computer vision techniques with an emphasis on higher level processes such as behaviour modelling and event detection. We conclude with a review of the evaluative mechanisms that have grown from within the computer vision community in an attempt to provide some form of robust evaluation and cross-system comparability.     

A survey of applications of threshold cryptography—proposed and practiced

ABSTRACT

Threshold cryptography is a secret sharing technique that finds applications in many fields including cloud computing, authentication, the Internet of Things, ad-hoc and sensor networks, digital signatures, and electronic voting. The technique can effectively reduce the total number of cryptographic keys used for encryption in a group. The article surveys the multifaceted applications of threshold cryptography, portraying the techniques and the secret sharing schemes used. The article also emphasizes the immediate need for reviving the expired Internet Engineering Task Force (IETF) draft of 2010 to establish a threshold cryptography standard.     

Intelligent retrieval and classification in three-dimensional biomedical images — A systematic mapping

The massive generation of data has raised new research topics, such as methods to store and to retrieve large volumes of information. Some medical image modalities, such as Magnetic Resonance Imaging, generate hundreds images series and many research groups have presented studies to develop intelligent techniques to classify and to retrieve this information. However, these studies are dispersed in several databases, and cataloged by using different terms. In this paper we present an analysis of these studies, through a Systematic Mapping that identifies methods and techniques currently being used in this scenario. In addition, we provide a perspective about the type of scientific literature the researchers have been disclosed their studies as well as impact on the scientific literature in dissemination of this knowledge domain. Some challenges and research opportunities are also highlighted in order to propitiate advances in the area.     

Hypermedia—introduction and survey

Our paper begins with an introduction to hypermedia presented with the example of a hypothetical hypermedia system. This is followed by an overview of the main hypermedia components visible to the user—data structures, authoring tools, navigation tools, and user interface. In the next section, we present a brief history of hypermedia, list applications in which hypermedia systems have been used, and describe several important commercial products and research projects. The last two sections introduce the major issues facing hypermedia technology and attempt to predict what direction it might take in the near future.     

Texture databases – A comprehensive survey

Texture analysis is a very important area in the field of computer vision and related fields. There are a good number of databases developed by different research groups for various texture analysis, in the field of medical analysis, robotics, recognition, analysis, image processing, etc. However, till-to-date, there is no comprehensive works covering the important databases and analyze these in various perspectives. In this paper, we consider this important task so that it becomes helpful for a researcher to choose and evaluate having crucial evaluating aspects in mind. We categorize and critically survey based on many references of the state-of-the-art related to the databases and other texture works. We strongly believe that this elegant survey will be a great contribution for the vision community, especially in the arena of texture analysis.